A number of genome-wide association studies (GWAS) have successfully implicated common SNPs in the etiology of complex traits. Most variants identified so far confer relatively small increments in risk (1.1-1.5-fold), and explain oly a small proportion of familial clustering. Recent studies have demonstrated that common diseases can be due to dysfunctional variants with a wide spectrum of allele frequencies. So far, rare variants studies have been limited to a handful of phenotypes and genes, but the advancement of sequencing technologies should lead to widespread association studies of candidate genes and genomes. If rare variants have larger effects than common variants, this should aid in their detection. Also their identification should have a greater impact on risk assessment, disease prevention and treatment. However, the analysis of rare variants is challenging since methods used for common variants are underpowered. Previously, we used data from mutation screening of breast cancer patients and controls to demonstrate the ability to detect evidence of pathogenicity from both truncating and splice junction variants and rare missense substitutions. The method involves stratifying rare missense substitutions observed in cases and/or in controls into a series of grades ordered from least to most likely to be evolutionarily deleterious, followed by a logistic regression trend test to compare the frequency distributions of the grades of variants in cases versus controls. The original model was developed to assess the pathogenicity of missense substitutions in breast cancer-related genes. Here we propose to test the efficiency of our analysis strategy to cutaneous malignant melanoma (CMM). To identify novel risk alleles, we will mutation screen the strongest candidate genes of the pigmentation pathway in over 1,300 cases and 1,300 matched controls from 10 European countries enrolled in the EPIC cohort. CMM provides a unique model for studies of gene-gene and gene-environmental interactions in the development of multifactorial diseases, since relationships between the major environmental factor (exposure to solar UV radiation) and known susceptibility genes are reasonably well understood. High-risk mutations in CDKN2A and CDK4 are carried by about 20-25% of melanoma-prone families. In contrast, some missense substitutions in the pigmentation gene MC1R have been proven to be modest-risk or intermediate-risk susceptibility alleles, and also to increase the penetrance of CDKN2A mutations. Finally, two recent GWAS identified low- penetrance SNPs in MC1R or in genes of the same pathway. Associated SNPs will account for no more than 12% of the Familial Relative Risk. Thus, the majority of the genetic susceptibility to CMM remains to be explained. After validation of our method on strong candidates, massive parallel sequencing of genes of entire biochemical pathways is envisaged to generate a comprehensive picture of the risk-frequency spectrum for pathogenic sequence variants involved in susceptibility to melanoma.